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Modeling the demand and supply in a new B2B-upstream market using a knowledge updating process

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  • Krishnan, Trichy V.
  • Feng, Shanfei
  • Beebe, Tony
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    Abstract

    Business-to-Business (B2B) services companies invest heavily in acquiring very expensive assets that they hire out to serve their clients (e.g. UPS buys huge warehouses and hires them out to companies), and hence they engage in careful long-term planning and forecasting, especially when it concerns a new market. It is interesting to note that the client-firms, on the other hand, decide to hire those assets based mostly on the prevailing short-term market forces. Hence, it is important for the companies which provide the assets for hire to also build the prevailing short-term market trends into their long-term forecasting and planning. In this paper, we develop a model for tracking these two simultaneously evolving and interacting patterns, namely the asset-availability (i.e. supply) and utilization (i.e. demand) patterns, in order to better understand the underlying processes, and thereby provide a basis for better forecasting. We test our models using three sets of data collected from the oil drilling industry, and find the proposed model to provide a good fit and forecasting efficiency.

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    Bibliographic Info

    Article provided by Elsevier in its journal International Journal of Forecasting.

    Volume (Year): 27 (2011)
    Issue (Month): 4 (October)
    Pages: 1160-1177

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    Handle: RePEc:eee:intfor:v:27:y:2011:i:4:p:1160-1177

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    Web page: http://www.elsevier.com/locate/ijforecast

    Related research

    Keywords: Marketing B2B service Knowledge updating Demand and supply Oil drilling;

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    References

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    1. Kenneth S. Corts, 2004. "The Effect of Repeated Interaction on Contract Choice: Evidence from Offshore Drilling," Journal of Law, Economics and Organization, Oxford University Press, vol. 20(1), pages 230-260, April.
    2. Frank M. Bass & Trichy V. Krishnan & Dipak C. Jain, 1994. "Why the Bass Model Fits without Decision Variables," Marketing Science, INFORMS, vol. 13(3), pages 203-223.
    3. Porter, Robert H, 1995. "The Role of Information in U.S. Offshore Oil and Gas Lease Auctions," Econometrica, Econometric Society, vol. 63(1), pages 1-27, January.
    4. Hendricks, Kenneth & Porter, Robert H, 1992. "Joint Bidding in Federal OCS Auctions," American Economic Review, American Economic Association, vol. 82(2), pages 506-11, May.
    5. Dipak Jain & Vijay Mahajan & Eitan Muller, 1991. "Innovation Diffusion in the Presence of Supply Restrictions," Marketing Science, INFORMS, vol. 10(1), pages 83-90.
    6. Tülin Erdem & Michael P. Keane, 1996. "Decision-Making Under Uncertainty: Capturing Dynamic Brand Choice Processes in Turbulent Consumer Goods Markets," Marketing Science, INFORMS, vol. 15(1), pages 1-20.
    7. P. B. Seetharaman, 2004. "Modeling Multiple Sources of State Dependence in Random Utility Models: A Distributed Lag Approach," Marketing Science, INFORMS, vol. 23(2), pages 263-271, April.
    8. Brannas Kurt & Nordstrom Jonas, 2004. "An Integer-Valued Time Series Model for Hotels that Accounts for Constrained Capacity," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 8(4), pages 1-11, December.
    9. Hendricks, Kenneth & Porter, Robert H, 1996. "The Timing and Incidence of Exploratory Drilling on Offshore Wildcat Tracts," American Economic Review, American Economic Association, vol. 86(3), pages 388-407, June.
    10. Paddock, James L & Siegel, Daniel R & Smith, James L, 1988. "Option Valuation of Claims on Real Assets: The Case of Offshore Petroleum Leases," The Quarterly Journal of Economics, MIT Press, vol. 103(3), pages 479-508, August.
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